c 3T3 cells

Toxicology in Vitro 23 (2009) 148–157

Contents lists available at ScienceDirect

Toxicology in Vitro journal homepage: www.elsevier.com/locate/toxinvit

Identification of tumor promotion marker genes for predicting tumor promoting potential of chemicals in BALB/c 3T3 cells Hideki Maeshima *, Katsutoshi Ohno, Yukimasa Tanaka-Azuma, Shigeru Nakano, Toshihiro Yamada Food Safety Research Institute, Nissin Food Products Co., Ltd., 2247, Noji-Cho, Kusatsu, Shiga 525-0055, Japan

a r t i c l e

i n f o

Article history: Received 27 March 2008 Accepted 16 October 2008 Available online 1 November 2008 Keywords: DNA microarray In vitro screening assay Molecular marker Transformation assay Tumor promotion

a b s t r a c t Tumor promoters can cause development of tumors in initiated cells and the majority of them are nongenotoxic carcinogens. The detection of tumor promoters is important for the prevention of cancer. The in vitro two-stage transformation assay, using BALB/c 3T3 cells, is a useful system, and benefits from a convenient protocol and high predictability of mammalian carcinogenicity. But these assays are timeconsuming and often require expertise for microscopic observation. To construct an in vitro tumor promoting activity test system, we performed large-scale gene expression analyses, using DNA microarrays, of BALB/c 3T3 cells following treatment with nine chemicals that are known to induce tumor promotion: TPA, zinc chloride, sodium orthovanadate, okadaic acid, insulin, lithocolic acid, phenobarbital sodium, sodium saccharide, sodium arsenite. As a result of DNA microarray and real time PCR analyses, 22 marker genes were identified. These consisted of genes related to cell cycle, regulation of transcription, antiapoptosis, and positive regulation of cell proliferation. There was a correlation between these 22 marker genes and the cell transformation assay results in BALB/c 3T3 cells. These results suggest that this tumor promoting activity test system, based on 22 marker genes, can become a valuable tool for screening potential tumor promoters. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction It is widely accepted that multiple mechanisms underlie the two main stages of carcinogenesis, initiation and promotion (Barrett, 1993; Hennings and Boutwell, 1970; Slaga, 1983; Weisburger and Williams, 1983). Initiators induce changes in DNA and can be detected by various short-term genotoxicity screening tests (Ames et al., 1973; Clive and Spector, 1975; Oda et al., 1985). Tumor development, in initiated cells, can be caused by repeated exposure to tumor promoters. There are many tumor promoters that are non-genotoxic (epigenetic) and their detection is an important approach for the prevention of cancer. The promotion stage of carcinogenesis is believed to occur primarily through epigenetic mechanisms (Barrett, 1993; Digiovanni, 1992; Williams, 1983). The phorbol ester tumor promoter, 12-O-tetradecanoylphorbol 13-acetate (TPA), stimulates cell proliferation through the rapid activation of protein kinase C (PKC) (Castagna et al., 1982; Niedel et al., 1983; Kikkawa et al., 1983). But the non-TPA tumor promoter, okadaic acid, does not bind to PKC, and inhibits serine/thre-

Abbreviations: TPA, 12-O-tetradecanoylphorbol-13-acetate; p,p’-DDE, 2,2-bis (4chlorophenyl)-1,1-dichloroethylene; MNNG, N-methyl-N’-nitro-N-nitrosoguanidine; TGFb 1, transforming growth factor b 1. * Corresponding author. Tel.: +81 77 561 9115; fax: +81 77 561 9140. E-mail address: [email protected] (H. Maeshima). 0887-2333/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.tiv.2008.10.005

onine protein phosphatases (Bialojan and Takai, 1988; Fujiki et al., 1991). These genetically controlled signaling pathways are becoming clearer, but yet, there is no universal explanation for how tumor promoters work. In vivo rodent models remain the only reliable way for experimental investigation of the tumor promotion activity of chemicals to humans. However, the rodent carcinogenicity assay is expensive and time-consuming. While, several screening methods for the detection of tumor promoters have been proposed (Kakunaga, 1973; Reznikoff et al., 1973). The in vitro cell transformation assay is regarded as a model system for carcinogenesis in vivo (Combes et al., 1999). In particular, the in vitro two-stage transformation assay, using BALB/c 3T3 cells, is one such system, and benefits from a convenient protocol and from high predictability of mammalian carcinogenicity (IARC/NCI/EPA Working Group, 1985). Transformation assay using BALB/c 3T3 cells can simulate the process of twostage carcinogenesis, initiation, and promotion, and therefore potentially can detect not only initiation activity, but also promoting activity of chemicals. BALB/c 3T3 cells are very sensitive to post-confluence inhibition of cell division and to the induction of transformed foci by chemical carcinogens. But this assay is timeconsuming and often requires expertise for staining and for microscopic observation. As a result, this assay is poorly suited for screening large numbers of chemicals. So, we have explored methods, based on the in vitro two-stage transformation assay using

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

BALB/c 3T3 cells that would enable the primary screening of chemicals for in vitro tumor promoting activity. The emergence of microarray technology has enabled carcinogenesis to be investigated by the analysis of global gene expression profiles. Many investigators have applied microarrays to analyze gene expression profiles of in vivo rodent models, following with TPA treatment (Ridd et al., 2006; Riggs et al., 2005; Wei et al., 2003) or other tumor promoters (Ellinger-Ziegelbauer et al., 2007; Fielden et al., 2007; Nie et al., 2006). By contrast, in in vitro cell transformation assay, no report describes the gene expression profiles following treatment with tumor promoters of various structures and properties. Global gene expression profiles during the tumor promotion phase, induced by various tumor promoters, may provide significant insights into the molecular basis of this distinct type of tumor promotion. Additionally, the discovery of reliable molecular markers that predicts the tumor promoting activity of chemicals would be immediate benefit for the identification of hazardous chemicals. We, therefore, performed largescale gene expression profiling in BALB/c 3T3 cells that had been treated with various tumor promoters during the promotion phase of a transformation assay, an in vitro model of a two-stage carcinogenicity test in order to identify tumor promotion marker genes.

149

motion treatment, was added to the medium on day 7, 11, and 14. The highest test concentration of each chemical was determined by its cell viability and solubility. On day 25 cells were fixed with methanol and stained with Giemsa solution. Scoring of transformed foci was performed according to criteria that discriminate transformed foci by four morphological characteristics: (1) foci of more than 2 mm in diameter, (2) deep basophilic staining, (3) piling up of cells forming a dense multi-layer and (4) random orientation of cells at the edge of foci. Data were analyzed statistically using the Wilcoxon’s rank sum test to determine the statistical significance between group differences, with P < 0.05 considered significant. Assessment of tumor promotion activity were as follows, , negative: No significant differences and under 200% of the solvent control activity; +, slight: No significant differences and more than 200% of the solvent control activity; ++, moderate: Significant differences and under 50% of the positive control (TPA) activity; +++, severe: Significant differences and more than 50% of the positive control (TPA) activity. 2.4. RNA extraction

Chemicals tested in this study are listed in Table 1. All chemicals used were of the highest purity grade available.

About 48 h after test chemicals or solvent were added in the promotion phase, total RNA was extracted from cells using the QIAGEN RNeasy protocol (QIAGEN, Hilden, Germany), according to the manufacturer’s instructions. Before in vitro transcription, residual genomic DNA was removed from the total RNA by DNase I treatment (RNase-free DNase set; QIAGEN) Quantification of isolated RNA was performed using UV-spectroscopy and the quality was determined both by the A260/A280 ratio and by an Agilent bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).

2.2. Cell culture

2.5. Gene expression analysis using DNA microarrays

BALB/c 3T3, clone A31-1-1, cells (JCRB0601) were provided by the Health Science Research Resources Bank (Osaka, Japan). Cells were maintained in Eagle’s minimum essential medium (MEM, GIBCO, Invitrogen Corp., Carlsbad, CA, USA) supplemented with 10% (v/v) fetal bovine serum (FBS, GIBCO). Cells were incubated at 37 °C in a humidified atmosphere containing 5% CO2.

Three biological replicates were prepared for solvent control only. Three micrograms of purified total RNA were transcribed into cRNA, purified, and then used as templates for in vitro transcription of biotin-labeled anti-sense RNA. All protocols followed the recommendations of the manufacturer (Affymetrix, Santa Clara, CA, USA). Twenty micrograms of biotinylated anti-sense RNA preparation was fragmented, assessed by gel electrophoresis, and placed in a hybridization mixture containing four biotinylated hybridization controls (BioB, BioC, BioD, and Cre). Samples were hybridized for 16 h to Affymetrix mouse genome 430 2.0 microarrays (Affymetrix), which comprised over 45,000 probe sets. Microarrays were washed and stained using the instrument’s standard FS 450-0001 protocol, incorporating antibody-mediated signal amplification. Subsequently, the arrays were scanned using a GCS 3000 7G Scanner. After scanning, the images of all arrays were inspected for physical anomalies and for the presence of excessive background hybridization.

2. Materials and methods 2.1. Chemicals

2.3. A short-term two-stage cell transformation assay, using BALB/c 3T3 cells, for the prediction of tumor promoting activity of chemicals A cell viability assay, using the standard crystal-violet absorption method, was applied to dose range finding for cell transformation assay. BALB/c 3T3 cells were harvested in MEM/ 10% FBS at a density of 2  105 cells per 60 mm dish, and cultured for 2 days. Test chemicals were then added and cells treated for another 4 days. Cells were fixed with 10% formalin and stained with 1% crystal-violet (CV) solution. After extraction of the stained CV with 0.02 N HCl-50% ethanol, OD570 values were measured. The highest concentration of transformation assay was decided at the concentration, which did not inhibit cell growth less than 50% of control or promote cell viability more than 110% of control. The chemical-induced transformation assay was carried out as previously reported (Tsuchiya and Umeda, 1995). Exponentially growing BALB/c 3T3 cells were harvested in MEM/ 10% FBS at a density of 104 cells per 60 mm dish (Corning, Flanklin Lakes, NJ, USA) from 10 plates per condition (day 0). After 24 h incubation, 3-methylcholanthrene (MCA; 0.2 lg/mL) was added as the initiation treatment (day 1). On day 4, the medium was changed to DMEM/ F-12 supplemented with 2% FBS, 0.2% ITS-X (GIBCO) and 0.9 lg/mL transferrin (CALBIOCHEM, San Diego, CA, USA) medium (DFI2 F). Thereafter, DFI2F medium was changed twice per week. Concentrations of a test chemical to be used for the transformation assay were determined according to the cell viability results. The test chemical, as the pro-

2.6. Data analysis Raw data analysis and scaling were performed in GeneChip operating software 5.0 (Affymetrix), and normalization and further analysis in GeneSpring 7.3 (Agilent Technologies). For each hybridization, intensities were normalized in three steps, (1) data transformation, (2) normalization per chip, and (3) normalization per gene. (1) All values below 0.01 were set to 0.01, (2) each chip was normalized to the 50th percentile of the measurements, and (3) each gene was divided by the intensity of solvent control samples. The normalized values were used for further analyses. To identify major biological themes underlying altered genes, functional analyses were conducted by using DAVID (Database for Annotation, Visualization and Integrated Discovery) 2007 (http://david.abcc.ncifcrf.gov/, Dennis et al., 2003; Huang et al.,

150

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

Table 1 List of chemicals and their respective results in the in vitro two-stage transformation assay using BALB/c 3T3 cells. Chemicals

BALB/c 3T3 cell transformation assay Dose (lg/mL)

Name

Sourcea

CAS no.

TPA Mezerein Di(2-ethylhexyl) phthalate Zinc chloride TGFb1 Sodium orthovanadate Sodium saccharide Okadaic acid Sulfadimethoxine Butylated hydroxyanisole Lithocholic acid Phenobarbital sodium Stannos chloride dihydrate Kojic acid Insulin Sodium arsenite Cadmium chloride Phenacetin DL-alpha-tocopherol Progesterone Atrazine p,p’-DDE Perylene Benz[a]anthracene Chrysene 1-Nitronaphthalene Sodium ascorbate Naphthalene MNNG D-Mannitol DL-Menthol 1-Nitropyrene Phorbol L-Cysteine hydrochloride Eugenol Propyl gallate Butylated hydroxytoluene 2-tert-butylhydroquinone

S S S W W W W W W V S W W W S W W W N W W A W A W W S W N N J A I W W W W W

16561-29-8 34807-41-5 117-81-7 7646-85-7 13721-39-6 128-44-9 78111-17-8 122-11-2 25013-16-5 434-13-9 57-30-7 10025-69-1 501-30-4 9004-10-8 7784-46-5 10108-64-2 62-44-2 10191-41-0 57-83-0 1912-24-9 72-55-9 198-55-0 56-55-3 218-01-9 86-57-7 134-03-2 91-20-3 70-25-7 69-65-8 1490-04-6 5522-43-0 17673-25-5 52-89-1 97-53-0 121-79-9 128-37-0 1948-33-0

0.1 0.1 30.0 7.5 0.003 1.0 5000.0 0.0075 100.0 30.0 7.5 500.0 10.0 100.0 20.0 0.15 0.3 3.0 3.0 1.5 30.0 5.0 1.0 5.0 1.0 10.0 100.0 3.0 1.0 300.0 100.0 1.0 1.0 100.0 3.0 1.0 10.0 3.0

Result

+++ +++ +++ +++ +++ +++ ++ +++ ++ ++ ++ ++ +++ ++ ++ ++ +++ ++ + + + +

b

DNA microarray analysisc 1.5-fold

2.0-fold

Up

Down

Up

Down

3267

5053

1465

1029

2319

2022

884

158

2041 3675 3421

3548 4588 4144

842 1221 1391

393 993 804

1285 1711

1630 1644

377 413

144 118

1185 982

948 1011

289 283

62 63

1599

2467

497

142

a These chemicals were purchased from the following sources: A, Aldrich Chemical Co., Inc. (Milwaukee, WI, USA.); I, ICN Pharmaceuticals Inc. (Costa Mesa, CA, USA.); J, Sigma–Aldrich Japan (Tokyo, Japan); N, Nacalai Tesque Inc. (Kyoto, Japan); S, Sigma–Aldrich Co., (St. Louis, MI, USA.); V, Avocado Research Chemicals Ltd., (Lancashire, UK); W, Wako Pure Chemical Industries Ltd., (Osaka, Japan). b Results of BALB/c 3T3 cell transformation assay were scored on a scale of 0–3 (+++, severe; ++, moderate; +, slight; , negative.). c Number of probe sets that were up- or down-regulated in BALB 3T3/c cells by ten chemicals as determined by DNA microarray analysis.

2007; Sherman et al., 2007). Functional annotation clustering uses an algorism to measure the relationship between the annotation terms based on the degree of their co-association genes to group the similar, redundant, and heterogeneous annotation contents from the same or different resources into annotation group. The enrichment score of each group is measured by the geometric mean of the EASE Scores (modified Fisher exact) (Hosack et al., 2003) associated with the enriched annotation terms that belong to this gene group. A higher score for a group indicates that the group members are involved in more important (enriched) roles.

reactions were performed in 96 well optical plates and run in an Applied Biosystems 7500 Real Time PCR System for 40 cycles at 95 °C for 15 s, 60 °C for 60 s. To quantify the results obtained by real time RT-PCR, we use the relative standard curve method. The amount of the expression of both target gene and endogenous gene (b-actin) in a sample were measured by comparing its amplification with the amplifications of standard curve. Then, the target amount is divided by the endogenous reference amount to obtain a normalized target value. Each of the normalized target values is divided by the solvent control (DMSO) normalized target value to generate the relative expression levels.

2.7. Quantitative real time RT–PCR 3. Results Primers were designed with Primer Express 3.0 software (Applied Biosystems, Foster City, CA, USA), and are listed in Table 2. Total RNA samples (200 ng) were reverse transcribed to yield first-strand cDNA using the Applied Biosystems Reverse Transcription Reagents protocol (Applied Biosystems). The reverse transcription reactions were then diluted 1:10 in distilled H2O. For individual reactions, 5 lL of each sample were combined with 20 lL of SYBR Green PCR Master Mix (Applied Biosystems) containing the appropriate primer pair at 6.5 lM. SYBR Green PCR

3.1. A short-term, two-stage cell transformation assay, using BALB/c 3T3 cells, for the prediction of tumor promoting activity of chemicals BALB/c 3T3 cells were initiated with 3-methylcholanthrene, and then treated for two weeks with each of the following chemicals: TPA, zinc chloride, sodium orthovanadate, sodium saccharide, okadaic acid, lithocolic acid, phenobarbital sodium, insulin, or sodium arsenite. These chemicals have various structures, and properties,

Table 2 List of candidate markers for tumor promoting activity and sequence of forward and reverse primers for quantitative real time PCR analysis. Gene symbol

Gene title

Accession no.

Forward primer

Reverse primer

Cell cycle

Ccnb1 Rif1 Mcm3

Cyclin B1 Rap1 interacting factor 1 homolog (yeast) Minichromosome maintenance deficient 3 (S. cerevisiae)

NM_172301 NM_175238 NM_008563

GCAGCACCTGGCTAAGAATGT CAGGACTGTCTCCACGGATGA CCCAGGACTCCCAGAAAGTG

TTCTTGACAGTCATGTGCTTTGTG GGGTATCTAGGGTCACAGGTTCA GAGGGCCGCCTTAAAAGC

G2/M transition of mitotic cell cycle

Chek1

Checkpoint kinase 1 homolog (S. pombe)

NM_007691

CCGACTTTCTAAGGGTGATGGA

CGCTGAGCTTCCCTTTAATCTTC

Regulation of transcription, DNA-dependent

Jun Junb Fosl1

Jun oncogene Jun-B oncogene Fos-like antigen 1

NM_010591 NM_008416 NM_010235

ATTGCTTCTGTAGTGCTCCTTAACAC GCCCTGGCAGCCTGTCT CCGAAGAAAGGAGCTGACAGA

TGCAGTCTAGCCTGGCACTTAC GCGCCAAGGTGGGTTTC CGATTTCTCATCCTCCAATTTGT

Anti-apoptosis

Hells

Helicase, lymphoid specific

NM_008234

TCTAGAATTACTGTTGGATCGAAGTGA

TCCCTGTCTTCCCTTTAATTGG

Angiogenesis

Vegfa

Vascular endothelial growth factor A

NM_009505

TGCACCCACGACAGAAGGA

TCGCTGGTAGACATCCATGAAC

Positive regulation of cell motility

Stmn1

Stathmin 1

NM_019641

CCCACAAAATGGAGGCTAACA

TCCACGTGCTTGTCCTTCTCT

Positive regulation of cell proliferation

Prl2c3

Prolactin family 2, subfamily c, member 3

NM_011118

GCCACAGACATAAAGAAAAAGATCAAC

TCTTCTTTTCTTCATCTCCATTCTGA

Endothelial cell proliferation

Scarb1

Scavenger receptor class B, member 1

NM_016741

GCCAAGCTATAGGGTCCTGAAG

GACTGGGTGGCTGGTCTGA

Ossification

Phex

NM_011077

GCCAAGAGAAATGGGAAAGCT

AGCACAAAACCTGTCCTTCCA

Dmp1

Phosphate regulating gene with homologies to endopeptidases on the X chromosome (hypophosphatemia, vitamin D resistant rickets) Dentin matrix protein 1

NM_016779

CCAGAGGGACAGGCAAATAGTG

GCCCAGCTCCTCTCCAGATT

Transport

Orm1 Orm2 Nup54 Slc2a1

Orosomucoid 1 Orosomucoid 2 Nucleoporin 54 Solute carrier family 2 (facilitated glucose transporter), member 1

NM_008768 NM_011016 NM_183392 NM_011400

ACTCCACCCATCTAGGATTCCA ACCTTACCCCCAACTTGATAAATG AGATGCAGACCTGTTACGAGAAATC TCCAACTGGACCTCAAACTTCA

GCAAAGGTTTCTACTCCTCCTTCA ACAGTGGTCATCTATGGTGTGATACTC TCAAGTGGCTAAGGCCTTCCT CCGCACAGTTGCTCCACATA

Positive regulation of Wnt receptor signaling pathway

Zeb2

Zinc finger E-box binding homeobox 2

NM_015753

GTGACAAGACATTCCAGAAAAGCA

TGGTGTGGTCTCTTTCCTGTGT

Translation

Rad21

RAD21 homolog (S. pombe)

NM_009009

GGTCTTCAGCGAGCTCTTGCTA

CGACACAGCTCAAGCAAACTG

DNA methylation

Il1rl1

Interleukin-1 receptor-like 1

NM_001025602; NM_010743

CTGCAGGAAAAGAGAATCCAAAC

GGAAGGCATTGTGGAATCAAG

DNA recombination

Rad51ap1

RAD51 associated protein 1

NM_009013

TGAAAGCAAGAGGCCCAAGT

AATGCATTGCTGCTAGAGTTCCT

Endocytosis Somitogenesis One-carbon compound metabolism

Tfrc Ab1 Car13

Transferrin receptor Abl-interactor 1 Carbonic anhydrase 13

NM_011638 NM_019501 NM_024495

TTGAGGCAGACCTTGCACTCT AAAATTCTCTGACCTTTAATCCTATGGT TTGAGAGTGTCACGTGGATTGTT

AAAGCCAGGTGTGTATGGATCA TGCCCACATGTAAAGCCATTAC CACAAGAGGCTTCGGAATCTG

Unknown

Pik3r5 6530403A03Rik

Phosphoinositide-3-kinase, regulatory subunit 5, p101 RIKEN cDNA 6530403A03 gene

NM_177320 NM_026382

GCAGAGTGTGGTCAGGTGTGA ATTGAAAATGACAGTGACCTGTTTG

GGTGGCAAGCTGCTCTTCTC GGACTTTTTCGGCTATTATCTTGATT

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

Gene ontology

151

152

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

including tumor promoter activity in vitro. Transformed foci were counted as an indication of tumor promoting activity. As a result, all chemicals including TPA, which is a typical tumor promoter, increased the number of transformed foci in a dose dependent manner, and were judged moderate to severe (Table 1 and Fig. 1). Sodium ascorbate, which does not have cell transformation activity, was also tested in a range of concentrations from 1–100 lg/ mL. And it did not increase the number of transformed foci, and was judged negative in this study. 3.2. Large-scale DNA microarray gene expression analysis and selection of candidate marker genes of in vitro tumor promotion To search for marker genes of in vitro tumor promoting activity, we analyzed global gene expression using DNA microarrays, after treatment with 11 different conditions. Nine different kinds of tumor promoters were used: TPA, zinc chloride, sodium orthovanadate, sodium saccharide, okadaic acid, lithocolic acid, phenobarbital sodium, insulin, sodium arsenite. And sodium ascorbate, which did not have cell transformation activity in this study, and solvent (DMSO) were also used as controls. Initially, to decide the time of total RNA collection, we used quantitative RT-PCR to analyze the gene expression time course of immediate early genes (Jun, Myc) and of the cell cycle related gene, Cyclin D1, which is a known carcinogenesis-related gene. Expression levels of these genes were higher compared to solvent control 48 h after the addition of several kinds of tumor promoters (data not shown). The collection time of total RNA was, therefore, set at 48 h after the addition of chemicals. Concentrations of test chemicals used for DNA microarray analysis are listed in Table 1. All chemicals were used at concentrations that produced the maximum number of foci in the cell transformation assay (data not shown). We normalized the microarray data and determined gene expression relative to expression of the solvent control. The numbers of probe sets that were up or down-regulated by either 1.5-fold or by 2.0-fold, in comparison with solvent control, are listed in Table 1. As a result, the expression of many genes was altered. To gain insight into the functional aspects of the microarray data, we exploited the web based annotational tool, DAVID, to help identify functional themes between genes that showed 2-fold or more up- or 0.5-fold or less down-regulation following each tumor promoter treatment. The results showing the major functional clusters are listed in Table 3. By severe tumor promoters, TPA, zinc chloride, sodium orthovanadate, comparisons made by gene ontology (biological process) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis revealed that the genes up-regulated were assigned to cell cycle progression related terms, the genes down-regulated were assigned to

14

**

No. of foci / dish

12 10

**

6 4 2 0 3

To examine the alterations in candidate marker gene expression identified using DNA microarray, 38 chemicals (including 10 chemicals using DNA microarray) were evaluated by quantitative real time PCR and BALB/c 3T3 cell transformation assay. Thirty-eight chemicals, in which we can obtain information of carcinogenesis, include tumor promoters, non-tumor promoters, genotoxic carcinogens, and food additives (Table 5). The relative gene expression levels of the 27 candidates after 48 h when they had been treated with each 38 chemicals and results of cell transformation assay are shown in Table 4. As a result of cell transformation assay, the 22 chemicals induced transformed foci. These chemicals increased the candidate marker gene expressions. But no gene completely corresponded with the results of cell transformation assay. In addition, detection of chemicals that induced transformed foci by each of the three genes (Zeb2, 6530403A03, Rad21) were limited to only 25% or less. Two genes (Junb and Dmp1) up-regulated some non-tumor promoters. Therefore, we have eliminated these 5 genes, and finally chosen the following 22 genes (Orm1, Scarb1, Stmn1, Nup54, Jun, Ab1, Slc2a1, Prl2c3, Fosl1, Chek1, Pik3r5, Vegfa, Rif1, Il1rl1, Phex, Tfrc, Rad51ap1, Hells, Mcm3, Orm2, Car13, Ccnb1), which had detect many tumor promoters and did not detect nontumor promoters.

4. Discussion

8

1

3.3. Quantitative real time RT-PCR analysis of candidate markers of in vitro tumor promoting activity and selection of tumor promotion markers

**

**

control

cell adhesion related term. But the genes up-regulated by other tumor promoters, okadaic acid, insulin, lithocolic acid, phenobarbital sodium, sodium saccharide, sodium arsenite, were assigned to various signaling pathway terms. In particular, in the genes down-regulated, there were neither common functional terms nor common genes (Table 3). Therefore, we focused on up-regulated genes, and selected candidate marker genes by sequentially applying the following criteria. Firstly we identified 6709 genes that gave reliable expression values and that showed increased expression of more than 1.5times the control, following treatment with the 9 tumor promoters. Secondly, from these genes, we identified 325 genes that showed an expression increase of more than 1.5-times the control, following treatment with more than five of the nine tumor promoters examined and that did not show an expression increase of more than 1.5-times following sodium ascorbate treatment. Thirdly, from 325 genes, we selected 27 genes that increased its expression in human or rodent cancer, and also showed high relative gene expression after treatment with tumor promoters that produced low levels of foci. These genes are thought to be either oncogenes, involved in the cell cycle, apoptosis obstruction, or cell proliferation. The resulting 27 genes are listed and categorized in Table 2.

10

30

100

TPA ng/ mL Fig. 1. A short-term two-stage cell transformation assay using TPA, a typical tumor promoter. BALB/c 3T3 cells were treated with TPA for 72 h after initiation with 3methycholanthrene (MCA, 0.1 lg/ml). **P < 0.01 (vs. control, Wilcoxon rank sum).

In this study, in order to identify tumor promotion marker genes, we performed a large-scale gene expression analysis, using DNA microarrays, on BALB/c 3T3 cells after they had been treated with each of 9 chemicals (TPA, zinc chloride, sodium orthovanadate, okadaic acid, insulin, lithocolic acid, phenobarbital sodium, sodium saccharide, sodium arsenite). Each of the nine chemicals are known to induce tumor promotion and each were treated in the promotion phase. As result of functional annotation clustering, severe tumor promoters TPA, zinc chloride, sodium orthovanadate showed typical tumor characters, such like cell cycle progression and loss of contact inhibition (Table 3). The expression of many genes was altered, but there was no gene that was commonly

Table 3 Functional annotation cluster analyses of up and down-regulated genes by nine tumor promoters. No. of up-regulated genes

Top 3 cluster determined from up-regulated genes

Enrichment score

No. of down-regulated genes

Top 3 cluster determined from down-regulated genes

Enrichment score

TPA

1465

Cell cycle Cell cycle process Response to DNA damage stimulus

41.80 21.46 12.03

1029

Cell adhesion Developmental process Regulation of cellular process

6.68 3.80 2.76

Zinc chloride

884

M phase Cell cycle process DNA metabolic process

39.49 16.30 12.77

158

Multicellular organismal development ECM-receptor interaction Extracellular matrix organization and biogenesis

3.35 2.95 2.51

Sodium orthovanadate

842

Cell cycle phase Cell cycle process DNA metabolic process

27.63 12.20 6.48

393

Biological adhesion Regulation of cellular process Multicellular organismal development

5.67 3.23 2.39

Okadaic acid

1391

Immune system process Inflammatory response Cell death

13.88 4.69 4.25

804

Metabolic process Biological regulation Regulation of developmental process

3.40 1.75 1.29

Insulin

289

Response to virus Positive regulation of JNK cascade Synaptogenesis

6.47 1.53 1.20

62

Metabolic process Cellular lipid metabolic process Biopolymer metabolic process

1.30 1.07 0.69

Lithocholic acid

377

Regulation of timing of cell differentiation Localization Cation transport

2.22 2.18 1.55

144

Response to virus Immune response Organ development

1.61 1.55 1.07

Phenobarbital sodium

413

Regulation of metabolic process Anatomical structure development

3.53 2.40

118

1.61 0.83

Acute-phase response

1.79

Cell division Microtubule cytoskelton Organization and biogenesis Lipid biosynthetic process

0.73

Sodium saccharide

1221

Cellular metabolic process Ribonucleoprotein complex biogenesis and assembly Carboxylic and metabolic process

11.64 7.04 5.82

993

Lung development Developmental process Regulation of progression through cell cycle

4.30 4.21 2.55

Sodium arsenite

283

G-protein signaling, coupled to cAMP nucleotide second messenger Cellular metabolic process Embryonic development

1.50

63

Negative regulation of transport

1.25

Transport I-kappaB kinase/NF-kappaB cascade

0.83 0.66

1.48 1.35

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

Chemicals

Note: Gene lists that showed 2-fold or more up- or 0.5-fold or less down-regulation, were applied to functional annotation clustering analyses. The clusters are ordered by group enrichment score. Cluster titles were obtained by selecting the overrepresented annotation that conveyed the broadest biological meaning from among the top three overrepresented annotations found in the cluster. A higher score for a group indicates that the group members are involved in more important (enriched) roles.

153

154

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

Table 4 Fold change values of candidate tumor promotion markers in BALB/c 3T3 cells determined by real time PCR and cell transformation assay results.

TPA

+++ 17.4 19.7 7.7

1.4

5.2 3.2 4.3 4.3 3.9 10.3 3.0 4.0 1.0 2.5

Mezerein

+++ 24.4 21.2 9.0

2.6

Zinc chloride

+++

9.7 2.7

3.4

Sodium saccharide

++

5.2

Rad21

6530403A03

Zeb2

Abi1

Rif1

Orm2

Car13

Chek1

Nup54

Hells

Mcm3

Stmn1

Rad51ap1

Vegfa

Scarb1

Junb

Tfrc

Pik3r5

Ccnb1

Phex

Jun

Slc2a1

Dmp1

Orm1

Fosl1

Prl2c3

Il1rl1

Chemicals

Transformation assay

Fold change values of candidate tumor promotion marker genes

4.6 2.2 4.5 4.7 1.9 4.1 1.4

0.7 2.2 1.6 1.4 1.4 1.9

1.6 2.4 3.1 4.3 6.5

8.5 2.3 5.6 1.8 1.5 10.4 3.8 7.5 6.4 2.0 5.7 1.4

0.5 1.9 1.0 1.0 1.6 1.7

1.1 1.7 2.9 3.9 5.8

2.0 2.5 2.9 2.0 1.4

5.6 3.5 3.6 3.3 1.1 2.8 2.1

1.6 1.7 1.6 1.2 1.4 1.9

3.9 53.5 4.9

3.2

1.0 2.5 2.8 4.4 0.7

2.8 1.9 3.3 3.4 3.7

1.4 2.3 2.3 2.8 2.1 1.7 0.9

0.7 2.6 1.3 1.8 2.5 1.6

-

5.1

4.0 2.9

1.0

0.6 1.7 0.7 5.5 3.2

3.0 3.8 2.7 1.4 3.2

4.4 2.6 2.2 3.4 2.2 3.2 1.4

0.8 3.0 1.7 1.4 2.3 2.0

Okadaic acid

+++

3.8

6.4 3.8

8.0

6.7 2.0 5.1 1.3 1.0

4.9 3.8 5.9 1.8 2.3

1.1 2.8 1.4 1.0 1.6 1.3 2.9

3.4 1.0 1.8 1.9 1.8 1.2

TGF1

+++

6.2

5.3 5.4

1.4 15.5 2.2 1.8 6.8 2.3

2.0 1.6 3.0 1.3 2.6

3.2 1.7 2.8 2.6 1.7 2.9 0.9

0.5 1.6 1.3 0.9 1.1 1.4

Sodium orthovanadate

+++

3.0 20.0 7.5

1.5

4.8 1.9 2.5 2.0 3.2

3.0 1.5 2.7 1.4 1.2

4.3 1.8 3.4 2.9 1.2 2.5 1.7

0.8 1.4 1.1 1.0 1.1 1.3

Phenobarbital sodium

++

1.6

2.1 1.2

7.2

3.3 1.7 2.7 2.4 0.8

1.9 1.1 1.4 1.2 2.2

0.7 1.4 1.1 1.1 1.6 1.2 1.8

4.4 1.6 1.7 1.6 1.6 1.3

Sulfadimethoxine

++

1.6

2.0 1.6

0.9

1.0 1.7 3.7 1.3 2.3

1.9 1.7 1.7 1.7 1.5

1.8 1.4 1.6 1.4 1.1 1.3 1.7

0.8 1.3 1.0 1.0 1.2 1.4

Lithocholic acid

++

0.6

0.7 1.3

5.8

2.4 1.9 3.8 1.1 1.6

1.8 1.7 2.6 1.7 3.0

1.3 1.6 1.1 1.4 1.1 1.4 1.3

4.3 1.2 1.3 1.6 1.1 1.4

Butylated hydroxyanisole

++

1.7

4.9 1.7

1.4

2.0 1.8 4.0 2.1 2.1

2.7 0.9 1.2 1.1 2.2

1.7 1.1 1.1 1.6 1.2 1.3 1.5

1.1 1.3 1.0 1.1 1.0 1.2

+

1.6

0.9 1.9 21.6

1.5 1.4 1.0 1.1 1.7

1.3 1.4 1.3 1.9 1.2

1.7 1.4 1.2 1.4 1.6 1.1 1.4 19.8 1.4 1.5 1.5 1.3 1.3

Butylated hydroxytoluene

Progesterone Insulin

++

1.7

2.2 1.8

2.0

1.5 1.3 1.4 1.9 1.6

1.4 1.4 1.2 1.3 1.4

1.4 1.4 1.7 1.4 1.3 1.4 1.4

1.5 1.3 1.4 1.3 1.3 1.3

Stannos chloride dihydrate

+++

1.0

2.6 2.1

2.5

2.2 2.2 1.1 2.4 1.2

1.2 2.5 1.1 1.6 1.5

1.4 1.0 1.1 1.2 1.1 1.3 1.2

1.2 0.8 1.1 0.8 1.1 1.1

Di(2-ethylhexyl) phthalate

+++

1.6

0.7 0.5

2.1

0.8 2.0 1.1 2.4 1.7

1.4 1.2 0.9 1.9 1.3

1.1 1.4 0.9 1.3 1.1 1.1 1.7

1.1 1.4 1.0 1.0 0.9 1.3

Sodium arsenite

++

1.4

2.0 1.5

1.7

0.9 1.2 0.9 1.7 1.3

1.1 1.5 1.3 1.2 1.4

1.4 1.4 1.4 1.3 1.4 1.3 1.2

1.1 1.2 1.5 1.2 1.2 1.1

Cadmium chloride

+++

1.1

6.0 1.9

1.8

1.9 1.2 1.4 2.2 1.3

1.0 1.0 1.1 1.1 0.9

1.4 0.9 1.1 1.4 0.8 1.2 0.8

1.1 0.8 0.6 0.6 1.0 0.9

Kojic acid

++

1.7

0.6 1.0

0.7

1.0 0.8 1.6 0.8 2.1

1.4 0.9 1.3 1.9 1.0

1.3 1.2 1.3 1.2 1.1 1.2 1.6

0.8 1.3 0.9 1.0 0.9 1.1

+

1.3

1.5 1.4

2.2

1.1 1.0 2.3 1.4 1.0

1.2 0.8 1.4 1.2 1.3

1.0 0.9 0.8 1.1 0.9 0.8 0.8

1.6 1.1 0.9 0.8 0.9 1.0

++

1.6

1.3 1.6

1.0

1.1 1.4 1.0 1.3 1.3

1.1 1.2 1.4 1.2 1.4

1.5 1.3 1.3 1.4 1.2 1.3 1.2

1.3 1.2 1.3 1.2 1.3 1.3

DL-alpha-tocopherol

+

1.0

0.8 0.8

1.7

1.1 1.2 2.1 1.2 1.1

1.3 0.8 1.4 1.0 1.1

0.9 1.1 0.9 1.0 1.2 1.0 1.3

1.2 1.2 1.0 1.2 1.0 1.3

p,p' -DDE

+

0.9

0.6 0.6

1.5

1.8 1.3 0.9 1.4 0.7

0.9 1.0 1.0 0.9 1.3

0.7 1.1 0.7 0.8 1.1 0.8 1.2

1.1 1.0 1.0 0.9 0.9 0.9

Perylene

-

1.0

0.5 1.6

0.6

0.5 0.9 1.0 0.6 1.0

0.9 0.8 1.3 1.4 1.3

1.1 1.3 1.1 1.1 1.2 1.1 1.1

0.5 1.1 1.3 1.0 1.2 1.0

0.6

0.3 0.6

1.1

1.6 1.1 1.0 0.5 0.3

0.7 1.0 1.2 1.1 1.3

0.5 0.8 0.7 0.6 1.2 0.7 1.0

1.0 1.0 1.0 1.2 1.3 0.9

1.0

0.7 0.9

1.4

1.4 1.0 1.1 0.7 0.7

0.8 1.1 1.6 1.2 1.2

0.8 1.0 1.0 0.9 1.2 1.0 1.3

1.2 0.9 1.0 1.2 1.4 0.9

Atrazine Phenacetin

Benz[a]anthracene Chrysene 1-Nitronaphthalene 2-tert-butylhydroquinone Naphthalene MNNG D-mannitol DL-Menthol 1-nitropyrene Sodium ascorbate Phorbol L-cysteine hydrochloride Eugenol Propyl gallate

1.2

0.8 1.2

1.0

1.7 1.2 1.4 0.7 1.2

1.3 1.0 1.4 1.3 1.4

1.0 1.2 1.0 1.1 1.3 1.2 1.2

0.7 1.1 1.0 1.3 1.3 1.1

1.1

0.7 1.0

0.9

1.1 0.9 1.4 0.6 1.2

1.0 0.9 1.3 1.1 1.1

1.1 1.2 1.0 1.0 1.0 1.0 1.1

0.9 1.0 1.0 1.1 0.9 1.0

0.9

0.5 0.7

1.3

0.9 1.0 0.9 0.9 0.9

1.1 0.9 1.2 1.0 1.2

0.7 1.0 0.9 0.9 1.2 0.9 1.0

0.9 0.9 1.0 1.1 1.4 1.0

1.0

0.7 0.8

1.3

1.1 0.9 1.0 1.0 1.3

1.1 0.8 1.2 0.9 1.0

1.0 1.0 1.0 1.0 1.1 0.9 1.0

0.8 0.8 1.0 1.1 1.3 0.9

0.9

0.8 0.8

0.9

0.8 0.8 0.9 0.9 0.9

1.0 0.8 1.1 1.0 0.9

0.8 0.9 0.8 0.9 1.1 1.0 0.9

0.9 0.9 0.9 1.0 1.2 0.8

1.0

0.9 0.9

0.9

1.4 0.9 1.2 1.0 0.9

1.1 0.8 1.3 0.9 1.1

0.8 0.9 0.8 1.0 0.9 0.9 0.9

0.9 0.9 0.9 1.1 1.0 0.9

0.7

0.4 0.6

1.0

1.4 0.7 1.0 0.4 0.5

0.7 0.6 1.0 0.9 1.1

0.4 0.7 0.6 0.6 0.9 0.7 0.9

0.9 0.9 0.9 1.0 1.3 0.9

1.4

0.6 0.7

0.6

1.1 0.7 1.1 0.7 0.9

0.8 0.5 0.9 1.1 1.0

0.8 1.0 0.9 0.8 0.9 0.8 1.2

0.9 0.9 0.8 1.0 0.8 0.8

1.4

1.1 1.1

0.9

0.9 1.0 1.1 1.2 1.2

1.0 1.3 1.1 1.1 1.0

1.0 1.0 1.0 0.9 1.0 0.9 1.1

1.1 1.1 1.0 0.9 0.9 1.0

1.2

1.1 0.9

0.7

0.7 0.7 0.9 0.8 0.8

1.0 0.7 1.0 0.9 0.8

0.7 0.8 0.7 0.8 0.9 0.7 0.9

0.5 0.9 0.9 1.0 0.8 1.0

1.0

1.0 1.2

1.1

1.1 1.1 1.2 1.1 1.0

1.3 1.2 1.4 1.0 1.4

1.1 1.2 1.1 1.1 1.2 1.1 1.1

1.3 1.2 1.3 1.2 1.1 1.1

0.7

0.4 0.5

1.1

0.9 0.9 0.9 0.8 0.5

0.9 1.0 0.9 0.7 1.3

0.6 0.9 0.7 0.7 1.1 0.6 0.9

1.2 1.1 1.2 1.3 1.0 1.0

Note: Real time PCR analysis was carried out after these cells were treated with the test chemicals for 48 h in promotion phase. Fold changes over 1.5, compared to solvent control, are color coded. Data were standardized against b-actin. BALB/c 3T3 cell transformation assays were scored on a scale of 0–3 (+++, severe; ++, moderate; +, slight; , negative).

Table 5 Tumor promoting activity of chemicals in vitro and in vivo tests and various cancer related tests. Chemicals

Published data

BALB/c 3T3 Cell transformation assay

In vivo tumor promoting activities

IARC

Reference

Reference

+ + + + + + + + + + + + + + + + + + + + + + +

+++ +++ +++ +++ +++ +++ ++ +++ ++ ++ ++ ++ +++ ++ ++ ++ +++ ++ + + + +

+ + + +

a

b

a

b

a

b

+ +

a

a

a

a

+ + +

a

b

a

b

a

a

b

+

a

+

a

3

+ +

a

1 2A

+ + +

a

Mutagenicity (Ames test)

Carcinogenicity in rodents Reference +

a

+

a

3

a

+

a

+

a

2B

a

+ + + + + +

a

+

a

+

a

a a a a

a

+ +

a a

a a a

+

a

a

+ + + + +

a

a

a

a a

a

+ +

a

a a

3

a

a a a a

a

+ +

a

3 3 2B 2B 3

a

+ +

a

a a

2B 2A

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

TPA Mezerein Di(2-ethylhexyl) phthalate Zinc chloride TGFb1 Sodium orthovanadate Sodium saccharide Okadaic acid Sulfadimethoxine Butylated hydroxyanisole Lithocholic acid Phenobarbital sodium Stannos chloride dihydrate Kojic acid Insulin Sodium arsenite Cadmium chloride Phenacetin DL-Alpha-tocopherol Progesterone Atrazine p,p’-DDE Butylated hydroxytoluene Perylene Benz[a]anthracene Chrysene 1-Nitronaphthalene Sodium ascorbate Naphthalene MNNG D-mannitol DL-Menthol 1-Nitropyrene Phorbol L-cysteine hydrochloride Eugenol Propyl gallate TBHQ

In vitro tumor promoting activities 22 Genes expression assay

a a

+

a

+

c

Equivocal Equivocal

a

2B

a c

+

a a

a

3

a a

Note: The results for the assessment of 22 genes expression assay are as follows, , negative: 1.5-fold up-regulated gene number under 2; +, positive: 1.5-fold up-regulated gene number more than 2. BALB/c 3T3 cell transformation assay were scored on a scale of 0–3 (+++, severe; ++, moderate; +, slight; , negative.). Published results of several tumor related tests are shown as +, , equivocal. a TOXNET CCRIS (database CCRIS from the cluster of toxicological databases TOXNET). b NTP (National Toxicology Program, Department of health and human services). c Koujitani et al. (2001).

155

156

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

Cell transformation result

20

; +++ ; ++ ;+ ;-

15

10

+++

+

Eugenol

Propyl gallate

Phorbol

L-cysteine hydrochloride

Sodium ascorbate

DL-Menthol

1-nitropyrene

MNNG

D-mannitol

Naphthalene

Chrysene

1-Nitronaphthalene

Benz[a]anthracene

Perylene

2-tert-butylhydroquinone

2,2-DDE

Butylated hydroxytoluene

Atrazine

DL-alpha-tocopherol

Progesterone

Kojic acid

++

Phenacetin

Insulin

Sodium arsenite

Lithocholic acid

Sulfadimethoxine

Butylated hydroxyanisole

Phenobarbital sodium

Cadmium chloride

Sodium saccharide

Di(2-ethylhexyl) phthalate

Okadaic acid

Stannos chloride dihydrate

Sodium orthovanadate

TPA

TGFβ1

0

Mezerein

5

Zinc chloride

Up-regulated gene numbers

25

-

Fig. 2. Correlation between cell transformation assay results and genes up-regulated by more than 1.5-fold compared to control. The data from 38 chemicals are listed in descending order of their cell transformation results (+++, severe; ++, moderate; +, slight; , negative) in the BALB/c 3T3 cell transformation assay. Each bar represents the number of genes that were more than 1.5-fold up-regulated compared to control, as assayed by real time PCR of BALB/c 3T3 cells after 48 h treatment.

changed by all the test chemicals. These data suggests that the mechanism of tumor promotion is very complex and that various signal transduction pathways are involved, at the time of 48 h after the addition of chemicals. It has been reported that the mechanism of tumor promotion includes some signal transduction pathways, such as inhibition of apoptosis, inhibition of gap-junctional intercellular communication, and induction of cell proliferation (Combes, 2000; Tomatis, 1993; Trosko and Ruch, 1998; Wright et al., 1994). Following treatment with more than five of the nine tumor promoters and also on previous reports of carcinogenicity 27 genes were selected, based on a 1.5-fold or more increase in expression (Table 2). Furthermore, we narrowed down the marker genes from 27 to 22 from the results of RT-PCR (Table 4). Some of these differentially expressed genes identified here have been reported previously to be up-regulated in rodent or human cancer. One of the major pathways that are routinely altered in most cancer types is cell cycle. Ccnb1 encodes the cell cycle-regulatory protein cyclin B1, which regulates the G2–M transition. Increased expression of Ccnb1 has association with lung, colorectal, prostate, breast, esophagus, and head and neck cancers (Soria et al., 2000). In this study, three genes (Ccnb1, Rif1, Mcm3) affecting this pathway were overexpressed by many tumor promoters (Table 4), contrary to the fact that confluence of BALB/c 3T3 cells usually induces cell cycle exit. It is thought that overexpression of these genes induces abnormal cell cycle progression in confluent cells. Recent evidence indicates that the inhibition of apoptosis as one of the function of tumor promoters. Hells encode a lymphoid specific helicase, one of the anti-apoptotic genes, which is thought to be involved with cellular proliferation and may play a role in leukemogenesis (Lee et al., 2000). The expression of this gene was upregulated by addition of some tumor promoters (8 of 23) (Table 4). Some tumor promoters obstruct apoptosis by raising the expression of Hells consequently may let the initiated cell survive. Jun (Jun protein family) together with Fosl1 (Fos protein family) are components of the AP-1 transcription factor. In this study, these genes were up-regulated in many tumor promoters (Table 4). This result is corresponding to the following reports. AP-1 transcription factor plays a key role in cell proliferation, cell differentiation,

apoptosis, tumorigenesis (Hess et al., 2004; Wagner, 2001) and is required for tumor promoter-induced cell transformation (Huang et al., 1998). Prl2c3 encodes prolactin family 2, subfamily c, member 3, which has hormone activity. It is reported that hormones, particularly the ovarian hormones and the prolactin clearly play a major role in the promotion of mammary tumorigenesis (Clevenger et al., 2003; Dao and Chan, 1983; Welsch and Nagasawa, 1977). Our experimental results are consistent with this, that Prl2c3 gene expression was up-regulated by addition of most of the tumor promoters (16 of 23) (Table 4). This genetic alteration may be the characteristic that many tumor promoters have. As well as the genes mentioned above, many genes are reported to have relation with cancer or cell proliferation in tumor promotion marker genes (Takahashi et al., 1995; Paciotti and Tamarkin, 1988). In this study, overexpression of the above-mentioned genes is thought to contribute to the generation of transformed foci. Therefore, it is thought that it has validity to assume these genes as tumor promotion marker. A practical goal of our study is to identify tumor promoter specific gene markers that could be used to establish an in vitro screening test based on gene expression. We identified 22 tumor promotion markers by DNA microarray and quantitative RT-PCR analyses. In order to establish a gene expression score, we counted the number of the marker genes that were up-regulated more than 1.5-fold by chemical treatment. The gene expression score was compared to the results of the cell transformation assay (Fig. 2). There was a correlation between the gene expression score and the results of the cell transformation assay using BALB/c 3T3 cells. In particular, the gene expression score showed a big increase in response to moderate to severe tumor promoters. Our results demonstrated that this gene expression score is a good index of tumor promoting potential for given chemicals. However, butylated hydroxytoluene was negative in the cell transformation assay, but resulted in a large number of up-regulated marker genes. Table 5 shows tumor promoting activity of chemicals in various cancer related tests. The antioxidant butylated hydroxytoluene is known to act as a typical tumor promoting agent in mouse lung (Witschi, 1986). Therefore, it is not surprising that butylated hydroxytoluene induced up-regulation of marker genes in our assay. This suggests

H. Maeshima et al. / Toxicology in Vitro 23 (2009) 148–157

that our gene expression score for the chemicals that were negative in the cell transformation assay are more similar to the results of in vivo tumor promotion tests compared to those of the cell transformation test. Our assay approach enables more sensitive assessment at an early time point and is easier to conduct than classical methods. A disadvantage is that it does not directly show tumor promoting activity as an altered phenotype, unlike the other tumor promoting tests. In addition, the present study focused on identification of marker genes. It is necessary to prepare independent test set to validate the performance of these marker genes. And further study on the mechanism of their functional role in the generation of transformed foci will be required. In conclusion, we have focused on early gene expression changes in BALB/c 3T3 cells that may assess tumor promoting activities of chemicals, and identified 22 marker genes. Consequently, it is suggested that this tumor promoting activity test system based on the expression of 22 marker genes can become a valuable tool for screening potential tumor promoters. Conflict of interest statement None declared. References Ames, B.N., Lee, F.D., Durston, W.E., 1973. An improved bacterial test system for the detection and classification of mutagens and carcinogens. Proceedings of the National Academy of Sciences of the United States of America 70, 782–786. Barrett, J.C., 1993. Mechanisms of multistep carcinogenesis and carcinogen risk assessment. Environmental Health Perspectives 100, 9–20. Bialojan, C., Takai, A., 1988. Inhibitory effect of a marine-sponge toxin, okadaic acid, on protein phosphatases. Specificity and kinetics. The Biochemical Journal 256, 283–290. Castagna, M., Takai, Y., Kaibuchi, K., Sano, K., Kikkawa, U., Nishizuka, Y., 1982. Direct activation of calcium-activated, phospholipid-dependent protein kinase by tumor promoting phorbol esters. The Journal of Biological Chemistry 257, 7847–7851. Clevenger, C.V., Furth, P.A., Hankinson, S.E., Schuler, L.A., 2003. The role of prolactin in mammary carcinoma. Endocrine Reviews 24, 1–27. Clive, D., Spector, J.F.S., 1975. Laboratory procedure for assessing specific locus mutations at the TK locus in cultured L5178Y mouse lymphoma cells. Mutation Research 31, 17–29. Combes, R., Balls, M., Curren, R., Fischbach, M., Fusenig, N., Kirkland, D., Lasne, C., Landolph, J., LeBoeuf, R., Marquardt, H., McCormick, J., Muller, L., Rivedal, E., Sabbioni, E., Tanaka, N., Vasseur, P., Yamasaki, H., 1999. Cell transformation assays as predictors of human carcinogenicity. The report and recommendations of ECVAM workshop 39. ATLA 27, 745–767. Combes, R.D., 2000. The use of structure-activity relationships and markers of cell toxicity to detect non-genotoxic carcinogens. Toxicology In Vitro 14, 387–399. Dao, T.L., Chan, P.C., 1983. Hormones and dietary fat as promoters in mammary carcinogenesis. Environmental Health Perspectives 50, 219–225. Dennis, G.J., Sherman, B.T., Hosack, D.A., Yang, J., Gao, W., Lane, H.C., Lempicki, R.A., 2003. Database for annotation, visualization, and integrated discovery. Genome Biology 4, R60. Digiovanni, J., 1992. Multistage carcinogenesis in mouse skin. Pharmacology and Therapeutics 54, 63–128. Ellinger-Ziegelbauer, H., Gmuender, H., Bandenburg, A., Ahr, H.J., 2007. Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies. Mutation Research 637, 23–39. Fielden, M.R., Brennan, R., Gollub, J.A., 2007. A gene expression biomarker provides early prediction and mechanistic assessment of hepatic tumor induction by non-genotoxic chemicals. Toxicological Sciences 99, 90–100. Fujiki, H., Suganuma, M., Yoshizawa, S., Nishiwaki, S., Winyar, B., Sugimura, T., 1991. Mechanisms of action of okadaic acid class tumor promoters on mouse skin. Environmental Health Perspectives 93, 211–214. Hennings, H., Boutwell, R.K., 1970. Studies on the mechanism of skin tumor promotion. Cancer Research 30, 312–320. Hess, J., Angel, P., Schorpp-Kistner, M., 2004. AP-1 subunits: quarrel and harmony among siblings. Journal of Cell Science 117, 5965–5973. Hosack, D.A., Dennis, G.J., Sherman, B.T., Lane, H., Lempicki, R.A., 2003. Identifying biological themes within lists of genes with EASE. Genome Biology 4, P4. Huang, C., Ma, W.Y., Young, M.R., Colburn, N., Dong, Z., 1998. Shortage of mitogenactivated protein kinase is responsible for resistance to AP-1 transactivation and transformation in mouse JB6 cells. Proceedings of the National Academy of Sciences of the United States of America 95, 156–161.

157

Huang, D.W., Sherman, B.T., Tan, Q., Collins, J.R., Alvord, W.G., Roayaei, J., Stephens, R., Baseler, M.W., Lane, H.C., Lempicki, R.A., 2007. The DAVID gene functional classification tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biology 8, R183. IARC/NCI/EPA Working Group, 1985. Cellular and molecular mechanisms of cell transformation and standardization of transformation assays of established cell lines for the prediction of carcinogenic chemicals: overview and recommended protocols. Cancer Research 45, 2395–2399. Kakunaga, T., 1973. A quantitative system for assay of malignant transformation by chemical carcinogens using a clone derived from BALB/3T3. International Journal of Cancer 12, 463–473. Kikkawa, U., Takai, Y., Tanaka, Y., Miyake, R., Nishizuka, Y., 1983. Protein kinase C as a possible receptor protein of tumor promoting phorbol esters. The Journal of Biological Chemistry 258, 11442–11445. Koujitani, T., Yasuhara, K., Tamura, T., Onodera, H., Takagi, H., Takizawa, T., Hirose, M., Hayashi, Y., Mitsumori, K., 2001. Lack of modifying effects of eugenol on development of lung proliferative lesions induced by urethane in transgenic mice carrying the human prototype c-Ha-ras gene. The Journal of Toxicological Sciences 26, 129–139. Lee, D.W., Zhang, K., Ning, Z.Q., Raabe, E.H., Tintner, S., Wieland, R., Wilkins, B.J., Kim, J.M., Blough, R.I., Arceri, R.J., 2000. Proliferation-associated SNF2-like gene (PASG): a SNF2 family member altered in leukemia. Cancer Research 60, 3612– 3622. Nie, A.Y., McMillian, M., Parker, J.B., Leone, A., Bryant, S., Yieh, L., Bittner, A., Nelson, J., Carmen, A., Wan, J., Lord, P.G., 2006. Predictive toxicogenomics approaches reveal underlying molecular mechanisms of non-genotoxic carcinogenicity. Molecular Carcinogenesis 45, 914–933. Niedel, J.E., Kuhn, L.J., Vandenbark, G.R., 1983. Phorbol diester receptor co-purifies with protein kinase C. Proceedings of the National Academy of Sciences of the United States of America 80, 36–40. Oda, Y., Nakamura, S., Oki, I., Kato, T., Shinagawa, H., 1985. Evaluation of the new system (umu-test) for the detection of environmental mutagens and carcinogens. Mutation Research 147, 219–229. Paciotti, G.F., Tamarkin, L., 1988. Interleukin-1 directly regulates hormonedependent human breast cancer cell proliferation in vitro. Molecular Endocrinology 2, 459–464. Reznikoff, C.A., Brankow, D.W., Heidelberger, C., 1973. Establishment and characterization of a cloned line of C3H mouse embryo cells sensitive to postconfluence inhibition of division. Cancer Research 33, 3231–3238. Ridd, K., Zhang, S.D., Edwards, R.E., Davies, R., Greaves, P., Wolfreys, A., Smith, A.G., Gant, T.W., 2006. Association of gene expression with sequential proliferation, differentiation and tumor formation in murine skin. Carcinogenesis 27, 1556– 1566. Riggs, P.K., Angel, J.M., Abel, E.L., Digiovanni, J., 2005. Differential gene expression in epidermis of mice sensitive and resistant to phorbol ester skin tumor promotion. Molecular Carcinogenesis 44, 122–136. Sherman, B.T., Huang, D.W., Tan, Q., Guo, Y., Bour, D., Liu, D., Stephens, R., Baseler, M.W., Lane, H.C., Lempicki, R.A., 2007. DAVID knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. BMC Bioinformatics 8, 426. Slaga, T.J., 1983. Overview of tumor promotion in animals. Environmental Health Perspectives 50, 3–14. Soria, J.C., Jang, S.J., Khuri, F.R., Hassan, K., Liu, D., Hong, W.K., Mao, L., 2000. Overexpression of cyclin B1 in early-stage non-small cell lung cancer and its clinical implication. Cancer Research 60, 4000–4004. Takahashi, Y., Kitadai, Y., Bucana, C.D., Cleary, K.R., Ellis, L.M., 1995. Expression of vascular endothelial growth factor and its receptor, KDR, correlates with vascularity, metastasis, and proliferation of human colon cancer. Cancer Research 55, 3964–3968. Tomatis, L., 1993. Cell proliferation and carcinogenesis: a brief history and current view based on an IARC workshop report. International Agency for Research on Cancer. Environmental Health Perspectives 101, 149–151. Trosko, J.E., Ruch, R.J., 1998. Cell–cell communication in carcinogenesis. Frontiers in Bioscience 3, 208–236. Tsuchiya, T., Umeda, M., 1995. Improvement in the efficiency of the in vitro transformation assay method using BALB/3T3 A31–1-1 cells. Carcinogenesis 16, 1887–1894. Wagner, E.F., 2001. AP-1 reviews. Oncogene 20, 2333–2497. Wei, S.J., Trempus, C.S., Cannon, R.E., Bortner, C.D., Tennant, R.W., 2003. Identification of Dss1 as a 12-O-tetradecanoylphorbol-13-acetate-responsive gene expressed in keratinocyte progenitor cells, with possible involvement in early skin tumorigenesis. The Journal of Biological Chemistry 278, 1758–1768. Weisburger, J.H., Williams, G.M., 1983. The distinct health risk analyses required for genotoxic carcinogens and promoting agents. Environmental Health Perspectives 50, 233–245. Welsch, C.W., Nagasawa, H., 1977. Prolactin and murine mammary tumorigenesis: a review. Cancer Research 37, 951–963. Wright, S.C., Zhong, J., Larrick, J.W., 1994. Inhibition of apoptosis as a mechanism of tumor promotion. The FASEB Journal 8, 654–660. Williams, G.M., 1983. Epigenetic effects of liver tumor promoters and implications for health effects. Environmental Health Perspectives 50, 177–183. Witschi, H.P., 1986. Separation of early diffuse alveolar cell proliferation from enhanced tumor development in mouse lung. Cancer Research 46, 2675–2679.